Social media has become widely used and along this widespread use has arisen a request to know locations related to users (for example residences or work places). For example, if a user sends disaster information, the location of the user can be quickly estimated and necessary measures can be taken. Furthermore, if the locations of users can be estimated, sales promotions targeted at each individual region will be possible. On the other hand, social media typically includes fields for users to fill in their profiles and make the user profiles public. However, only a small minority of users fill in their exact locations in the profile fields. For example, it has been reported that a little more than 20% of the users of a social media filled in their exact locations in the profile fields. Various approaches to circumventing the problem have been attempted. For example, an approach has been attempted in which latitude/longitude information called a geotag is added to information to be sent by users by using a GPS (Global Positioning System) function of a mobile device (see Non-patent Literature 3). Another technique has been proposed that analyzes a text in sent information to estimate a location from a geographical name contained in the text (see Patent Literatures 1 and 2).
A technique has been proposed that estimates the location of a user from regionality of words (words specific to a particular region and dialect) used in a posted text to estimate the location of the user (see Non-patent Literature 1). Another technique has been proposed that takes into consideration the relationship between users (follow/followed relationship) that is implemented in social media to estimate the location of a user on the assumption that regionality is reflected in the relationship (Non-patent Literature 2).    [Non-patent Literature 1] Cheng, et al. “You are where you tweet: A content-based approach to geo-locating Twitter users”. In proceedings of CIKM, 2010.    [Non-patent Literature 2] Clodoveu, et al. “Evaluation of the quality of an online geocoding resource in the context of a large Brazilian city”, Transactions in GIS, Volume 15, Issue 6, pp. 851-868, December 2011.    [Non-patent Literature 3] T. Sakamaki, et al. “User behavior pattern analysis using geotag of microblog”, IEICE Technical Report, NLC 2010-37.    [Patent Literature 1] JP2010-517147A    [Patent Literature 2] JP2008-158564A
However, these approaches have the following problems and the effects of the approaches are limited. First, in reality, text in information with a geotag and information sent rarely contains geographical names. Estimation of based on regionality of words and regionality of relationship between users cannot be precise enough.